Recent high profile outbreaks of verotoxigenic Escherichia coli (VTEC) and Listeriosis have brought food and water safety to the forefront of public concern. These outbreaks have highlighted the urgent need for rapid, sensitive and field deployable methods for pathogen detection and characterization in foodstuffs.
The detection and identification of bacterial contaminants in foodstuffs is currently an area of intense research and development. Currently, regulatory agencies make decisions regarding the removal of contaminated products from the supply chain using culture-based methods that are labor intensive and time consuming (5-9 days to detect bacterial pathogens). Most emerging technologies in this area focus on the specific detection and identification of bacterial strains using genetic material, but require large quantities of DNA/RNA and are unable to identify live bacteria from dead ones that are found abundantly throughout treated food samples. There is currently no rapid method for assaying whether a pathogenic material that might test positive in a PCR or antibody-based IVD test is alive or dead. This is required for regulators to take legal action and for suppliers to prevent legal action.
Metabolic labeling of microorganisms and bio-orthogonal click chemistry for the purpose of detection or glycoproteomic analysis is known in the art (e.g. Besanceney-Webler-2011; Yang 2010a; Yang 2010b; Yang 2011; Dumont 2012). However, such techniques often rely on the destruction of cells for further analysis and are therefore unsuitable for specific identification of live microorganisms. Methods of identifying bacteria are known (e.g. Akihiko 1995; Pollard 1995; Kulla 1994), which involve incorporating various radioactive or non-radioactive isotopes into bacterial cells followed by detection of the isotope. These methods are usually slow and tedious and often require destruction of cells to perform the analysis. Further, detection methods for bacteria employing the detection of metabolized substrates (e.g. Thacker 2002; Dukan 2013) have been used, but these methods suffer from a variety of limitations including the inability to separate live microorganisms from the sample leading to interferences and inaccuracies in the identification of microorganisms in the sample.
There remains a need for improved methods for detecting live microorganisms that provide faster identification, using less material and in a manner that can maintain the integrity of live bacteria for further identification analysis.